Text Analysis - Linguistics Meets Data Science
Instructions
Let us first start by summarising the previous introductory pages. Text analytics can be applied in many different forms and purposes. Whether you are from a background in data science or linguistics, we intend for this OER to show you something new to do or some new way of considering the texts you work with. If you approach this without any background in working with texts and language, we still hope that the OER will work as a primer and a welcome to the wonderful world of text analytics.
The OER aims to provide you with practical approaches for conducting text analytics while equipping you with the background and theoretical knowledge needed to understand WHY these approaches make sense. While the content is limited, we hope to have provided at least some information about the different considerations that go into this type of work and the broad strokes of how language can be approached. Consider the OER as an entry point and a way of getting your feet wet.
So what to do now? The OER is designed to be studied in order, as some lessons build upon one another. While you might already be familiar with a topic, giving the lesson a quick read is a good idea anyway. Terminology is a tricky beast, and we might have used a new term for a concept you already know. To avoid confusion, it might be best to not pick and choose between the lessons. Returning to previous lessons as you go along is also a good idea. After spending more time on the OER, concepts and ideas that initially seemed weird and complex might start to make more sense the second time.
We feel that it is essential for you to make room for yourself in this OER. While the examples and activities cover some interesting applications of text analytics, it is crucial that you also try to apply the methods to data and material that interests you personally (or professionally). Partially, this is a way for you to keep engaged with the OER throughout the duration, but it is also an important step towards becoming independent in your use of the methods. Taking a break and working on applying the OER's content to a personal project or tweaking an example to fit your use case is a great way to learn.
So get a notebook ready, start with the first lesson, and try to imagine how you could use the things you will learn about!
The OER aims to provide you with practical approaches for conducting text analytics while equipping you with the background and theoretical knowledge needed to understand WHY these approaches make sense. While the content is limited, we hope to have provided at least some information about the different considerations that go into this type of work and the broad strokes of how language can be approached. Consider the OER as an entry point and a way of getting your feet wet.
So what to do now? The OER is designed to be studied in order, as some lessons build upon one another. While you might already be familiar with a topic, giving the lesson a quick read is a good idea anyway. Terminology is a tricky beast, and we might have used a new term for a concept you already know. To avoid confusion, it might be best to not pick and choose between the lessons. Returning to previous lessons as you go along is also a good idea. After spending more time on the OER, concepts and ideas that initially seemed weird and complex might start to make more sense the second time.
We feel that it is essential for you to make room for yourself in this OER. While the examples and activities cover some interesting applications of text analytics, it is crucial that you also try to apply the methods to data and material that interests you personally (or professionally). Partially, this is a way for you to keep engaged with the OER throughout the duration, but it is also an important step towards becoming independent in your use of the methods. Taking a break and working on applying the OER's content to a personal project or tweaking an example to fit your use case is a great way to learn.
So get a notebook ready, start with the first lesson, and try to imagine how you could use the things you will learn about!